Objective To explore the impact of an intelligent monitoring nursing model based on wearable devices and machine learning on the early warning of postoperative complications and nursing efficiency in patients treated with total hip arthroplasty (THA).

Methods A total of 90 THA patients were selected, and divided into the observation group and control group according to the random number table method, with 45 cases in each group. The observation group adopted the intelligent monitoring nursing mode, while the control group adopted the conventional nursing mode. The occurrence of postoperative complications (deep vein thrombosis, infection, dislocation, pulmonary complications, etc.) and indicators of nursing efficiency (nursing response time, completion time of nursing records) were observed and compared between two groups.

Results The incidence of postoperative complications in the observation group was 8.89% (4/45), which was significantly lower than in control group33.33(15/45) (P ＜ 0.01). The nursing efficiency indicators such as the nursing response time and completion time of nursing records in the observation group were significantly better than those in control group (P ＜ 0.01).

Conclusions The intelligent monitoring nursing model based on wearable devices and machine learning can effectively provide early warning of postoperative complications, and significantly improve nursing efficiency in THA patients, and it is worthy of clinical promotion and application.